Evaluation and rectification system

ABSTRACT

Methods for customizing an educational experience of a gamer are provided. The method can include the generating of learning DNA which can include information relating to the gamer. The learning DNA can be generated by the aggregation of data received from the gamer, collected from other data sources, and generated based on the interaction of the user with an evaluation and rectification system. The method can further include selecting a mission for a user based on the learning DNA and/or information relating to the user.

CROSS-REFERENCES TO RELATED APPLICATIONS

This patent application is a continuation of U.S. patent applicationSer. No. 14/103,576, filed on Dec. 11, 2013, now U.S. Pat. No.8,753,200, issued on Jun. 17, 2014 and entitled “Evaluation andRectification System,” which claims the benefit of U.S. ProvisionalApplication No. 61/759,902, filed on Feb. 1, 2013, and entitled“Evaluation and Rectification System,” the entirety of which are herebyincorporated by reference herein.

BACKGROUND OF THE INVENTION

This disclosure relates in general, but not by way of limitation, todirected learning as within a Learning Management System (LMS), OnlineHomework System (OHS), and/or any other similar educational features,systems, or components such as, for example, a virtual learningenvironment (VLE) and a learning content management system (LCMS).

The advancement of a student through learning material is directed by asyllabus of curricula that organizes learning materials into ahierarchical structure. A syllabus divides subject areas into topics anddivides those topics into learning objectives. The syllabus creates arigid learning structure that outlines a single path for progressingthrough the learning material encompassed by the syllabus. Althoughsyllabi have been used for a long time, new methods, techniques, andsystems for directing learning are required.

BRIEF SUMMARY OF THE INVENTION

In one embodiment, the present disclosure provides a method forgenerating learning DNA. The learning DNA can be the aggregate ofgenerated and/or collected information for a gamer. This information canbe generated and/or received via gamer inputs, via gamer interactionwith an evaluation and rectification system, and/or from aggregators ofinformation relating to the gamer. In one embodiment, the generation oflearning DNA can include generating a gamer account, requesting gamerinformation such as, for example, the gamer age, gamer learning style,gamer knowledge and/or developed skills, and/or grade level, identifyingand receiving information from sources of gamer information, andreceiving mission information, which mission information can relate tomission started by the gamer, missions completed by the gamer, andthe/or to the degree of success with which the gamer completed themission. In some embodiments, the generation of the learning DNA canfurther include associating the above-mentioned information with thegamer account.

In one embodiment, the present disclosure relates to a method ofproviding a customized mission to a gamer. This can include generatinglearning DNA including a gamer age, a gamer education level, gamersubjects, and past mission results for the gamer. In some embodiments,the learning DNA can be generated by requesting information from thegamer, which requested information can include information about thegamer such as, for example, the gamer age, the gamer education level,gamer subjects, and/or past mission results for the gamer, andinformation identifying a source of information about the gamer. In someembodiments, the source of information about the gamer can be, forexample, any source of information relating to the gamer. This caninclude, for example, a source of education related information, asource of health related information, a source of demographicinformation, a source of economic information, and/or a source ofpersonal information. In some embodiments, generating the learning DNAcan include receiving information from the gamer, which informationreceived from the gamer can include information identifying a source ofinformation about the gamer and information about the gamer, which caninclude, for example, the gamer age; and the gamer education level. Insome embodiments, generating the learning DNA can include querying theidentified source of information about the gamer for gamer information.In some embodiments, the source of information can include one of asocial network, a learning management system, an education institute, asource of an online profile, a source of medical records, and a sourceof public records. Generating the learning DNA can include receivinginformation from the identified source of information about the gamer,and storing the received information. In some embodiments, the method ofproviding a customized mission to a gamer can include selecting amission having a subject matter corresponding to an aspect of thelearning DNA.

In one embodiment, the present disclosure relates to a system forproviding a customized mission to the gamer. The system can includememory storing a plurality of missions and memory that can store thelearning DNA. The system can include a processor that can, generatelearning DNA including a gamer age, a gamer education level, gamersubjects, and the gamer's past mission results. The learning DNA can begenerated by requesting information from the gamer, which requestedinformation can include information about the gamer and informationidentifying a source of information about the gamer, receivinginformation from the gamer, which information received from the gamercan include information identifying a source of information about thegamer and information about the gamer, the information about the gamerincluding at least one of: the gamer age; and the gamer education level.The learning DNA can be generated by querying the identified source ofinformation about the gamer for gamer information, which source ofinformation can include one of a social network, a learning managementsystem, an education institute, a source of an online profile, a sourceof medical records, and a source of public records. The learning DNA canbe generated by receiving information from the identified source ofinformation about the gamer, and directing the information received fromthe gamer and from the identified source of information about the gamerto the memory that can store the learning DNA. In some embodiments, theprocessor of the system can select a mission, which mission canencompass subject matter corresponding to an aspect of the learning DNA.

In some embodiments, the present disclosure relates to a method ofcustomizing a mission. The method can include identifying a gamer,identifying a gamer age and a gamer grade level, retrieving a databaseof subjects, which database can include information identifying aplurality of subjects and information identifying a plurality ofconditions indicating the applicability of the subject to one or severalcategories of gamers, identifying a sub-group of the plurality ofsubjects identified in the database, which subgroup can be identifiedaccording to at least one of: the gamer age, the gamer grade level, andthe gamer identification. The method can include receiving an inputidentifying one of the sub-group of the plurality of subjects, theidentified one of the sub-group of the plurality of subjects containinga plurality of topics, receiving a database of topics associated withthe identified one of the sub-group of the plurality of subjects,receiving an input identifying one of the plurality of topics, theidentified one of the plurality of topics containing subject matter,generating an evaluation, the evaluation including a plurality ofquestions relating to at least portions of the subject matter, andproviding a mission to a gamer based on gamer responses to theevaluation.

Further areas of applicability of the present disclosure will becomeapparent from the detailed description provided hereinafter. It shouldbe understood that the detailed description and specific examples, whileindicating various embodiments, are intended for purposes ofillustration only and are not intended to necessarily limit the scope ofthe disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is described in conjunction with the appendedfigures:

FIG. 1 depicts a block diagram of an embodiment of embodiment of anevaluation and rectification system;

FIG. 1A depicts a schematic illustration of an embodiment of a userdevice;

FIG. 2 is a flowchart illustrating one embodiment of a process forgenerating learning DNA;

FIG. 3 is a flowchart illustrating one embodiment of a process forretrieving gamer information;

FIG. 4 is a flowchart illustrating one embodiment of a process forupdating learning DNA based on mission results;

FIG. 5 a flowchart depicting one embodiment of a process for operating arecommendation engine to recommend a mission;

FIG. 6 is a flowchart depicting one embodiment of a process foridentifying information desired for making a mission recommendation;

FIG. 7 is a flowchart illustrating one embodiment of a process forgenerating an evaluation;

FIG. 8 is a flowchart illustrating one embodiment of a process foridentifying learning style;

FIG. 9 depicts a block diagram of an embodiment of a computer system;and

FIG. 10 depicts a block diagram of an embodiment of a special-purposecomputer system.

In the appended figures, similar components and/or features may have thesame reference label. Where the reference label is used in thespecification, the description is applicable to any one of the similarcomponents having the same reference label. Further, various componentsof the same type may be distinguished by following the reference labelby a dash and a second label that distinguishes among the similarcomponents. If only the first reference label is used in thespecification, the description is applicable to any one of the similarcomponents having the same first reference label irrespective of thesecond reference label.

DETAILED DESCRIPTION OF THE INVENTION

The ensuing description provides preferred exemplary embodiment(s) only,and is not intended to limit the scope, applicability or configurationof the disclosure. Rather, the ensuing description of the preferredexemplary embodiment(s) will provide those skilled in the art with anenabling description for implementing a preferred exemplary embodiment.It is understood that various changes may be made in the function andarrangement of elements without departing from the spirit and scope asset forth in the appended claims.

In one embodiment, the present disclosure provides an evaluation andrectification system including a processor, one or several databases,one or several user devices, and one or several data aggregators. Theevaluation and rectification system collects information from the one orseveral user devices and from the one or several data aggregators andgenerates learning DNA based on the collected data. The learning DNA isused to select a mission customized to the gamer.

In one embodiment, the present disclosure provides a method forcustomizing a mission to a gamer area for learning improvement. Themethod can include, for example, receiving information identifying thegamer's learning level, a subject, a topic within the subject, and thesubtopic within the topic. The method can include generating anassessment questionnaire including a plurality of questions associatedwith aspects of the subtopic, receiving gamer provided answers to thequestions of the assessment questionnaire, and providing a mission tothe gamer based on the correctness of the gamer provided answers.

In one embodiment, the present disclosure provides a method forcustomizing a mission to optimize the gamer's learning. The method caninclude, for example, receiving an indicator of the gamer's preferredlearning style, providing a first mission to the gamer, the firstmission being selected to match the gamer's indicated preferred learningstyle, providing a second mission to the gamer, the second mission beingselected to not match the gamer's indicated preferred learning style,and comparing the results of the first mission and the second mission togenerate an indicator of the relative effectiveness of the preferredlearning style and the non-preferred style. The method can include, forexample, providing a third mission to the gamer, the third mission beingselected to match the relatively more effective of the learning styles.

With reference now to FIG. 1, a block diagram of one embodiment of anevaluation and rectification system 100 is shown. The evaluation andrectification system 100 aggregates data relating to a gamer, andspecifically to a gamer's level of study, a gamer's comprehension level,and/or the gamer's learning style. The evaluation and rectificationsystem 100 can use the aggregated data to generate one or severalmissions. In some embodiments, for example, the missions can be used togenerate further gamer data to thereby identify areas of desiredimprovement in the gamer's comprehension level, to identify areas ofsatisfactory and/or excellent gamer comprehension, and/or to identifythe relative effectiveness of different learning styles. In someembodiments, for example, the missions can contribute to increasing thegamer's level of study, the gamer's comprehension level, and/or toincrease the effectiveness of gamer learning styles.

The evaluation and rectification system 100 can include a processor 102.The processor 102 can provide instructions to and receive informationfrom the other components of the evaluation and rectification system100. The processor 102 can act according to stored instructions, whichstored instructions can be located in memory associated with theprocessor and/or in other components of the evaluation and rectificationsystem 100. The processor 102 can comprise a microprocessor, such as amicroprocessor from Intel® or Advanced Micro Devices, Inc.®, or thelike.

The evaluation and rectification system 100 can include one or severaldatabases 104. The one or several databases 104 can comprise stored datarelevant to the functions of the evaluation and rectification system100. The one or several databases 104 can include a learning DNAdatabase 104-A. The learning DNA database 104-A can include learning DNAassociated with a user such as, for example, a gamer. This learning DNAcan include, for example, any information relating to the gamer, thegamer's level of education, the gamer's educational needs, a gamer areafor learning improvement, any of the gamer's learning abilities and/ordisabilities, learning styles, including, for example, preferredlearning styles, and the relative effectiveness of different learningstyles, and/or any gamer demographic information. The learning DNA canbe received from the gamer, from a non-gamer user of the evaluation andrectification system 100, and/or from other components of the evaluationand rectification system 100. In some embodiments, for example, thelearning DNA can be static in that it is not updated after itsgeneration, and in some embodiments, for example, the learning DNA canbe dynamic in that it is updated after its initial generation. Thelearning DNA can be used by the evaluation and rectification system 100to select missions for gamer.

The one or several databases 104 can include a missions database 104-B.The missions database 104-B can include information relating to one orseveral missions. The missions can include activities configured toteach a gamer information, to teach a gamer a skill, to ascertain agamer's mastery of some information and/or skill, to provide practicerelating to material, to determine the effectiveness of one or severallearning styles, to introduce the gamer to a new learning style, and/orto increase the ability of the gamer to learn with the learning style.The activities can include watching a video, listening to a lecture,reading material, receiving training, participating in an assessmentsuch as a test or a quiz, and/or the like. In some embodiments, forexample, the missions can include an audio component, a visualcomponent, tactile component, an interactive component, text, one orseveral questions, one or several questions and answers, one or severaltests, and/or one or several quizzes.

In some embodiments, for example, the missions can include a gamingcomponent. The gaming component can include, for example, the award ofpoints for the completion of the mission, for the completion of aportion of a mission, for the demonstrated mastery of the subject matterof a mission, or for correctly answering one or several questionsassociated with the mission. In some embodiments, for example, thegaming component can include, a storyline, an opponent, a protagonist,one or several tools and/or weapons, one or several abilities and/orskills, and/or a disposition based on the gamer performance such as, forexample, winning and/or losing.

The evaluation and rectification system 100 can include an accessdatabase 104-C. The access database 104-C can include securityinformation to secure access to the evaluation and rectification system100 and filter information provided by the evaluation and rectificationsystem 100.

In some embodiments, for example, the access database can comprise logininformation. This information can include, for example, informationidentifying a user such as, for example, a username and password, or auser identification number. In some embodiments, for example, when auser desires to access the evaluation and rectification system 100, theuser can be prompted to enter identification information such as, forexample, a username and password. After the user provides theidentification information, the evaluation and rectification system 100can verify the identification information, and specifically, theprocessor 102 can compare the user provided identification informationto information stored within the access database to determine if thecurrent user is an authorized user.

In some embodiments, after the processor 102 has determined whether theuser is an authorized user, the processor 102 can determine the user'saccess level. In some embodiments, for example, this determination caninclude querying the access database 104-C for access informationassociated with the user provided identification information. In someembodiments, for example, the access level can correspond to theportions of the learning DNA database 104-A that the user can accesssuch as, for example, limiting a gamer's access of the learning DNAdatabase 104-A to accessing their own learning DNA. In some embodiments,for example, the access level can correspond to portions of the missionsdatabase 104-B that a user can access such as, for example, allowing agamer to access missions corresponding to their subscription level,corresponding to their grade level, and/or corresponding to any otherfactor, and in some embodiments, the access level can correspond toallowing an administrator to access all or portions of the evaluationand rectification system 100 including the missions database 104-B toprovide updates and maintenance to the evaluation and rectificationsystem 100 and/or to some or all of the missions in the missionsdatabase 104-B.

In some embodiments, for example, information stored within the accessdatabase 104-C can be used to filter and/or limit learning DNA providedto the user device 106 such as, for example, the supervisor device 106-Cand/or to one or several of the data aggregators. In some embodiments,for example, the access database 104-C can include informationidentifying a supervisor associated with the gamer such as, for example,one or more of gamer's parents and/or teachers. The evaluation andrectification system 100 can use this information to provide informationupdating the supervisor on the gamer's status and/or progress within theevaluation and rectification system 100. In some embodiments, forexample, information from the access database 104-C can be used to limitinformation transmitted to the supervisor such as, for example,eliminating the gamer address, gamer medical records, and/or any otherdesired information. In some embodiments, for example, a similarfiltration of provided learning DNA can be performed before any portionof the learning DNA is transmitted to one or more of the dataaggregators 108.

The evaluation and rectification system 100 can include one or severaluser devices 106, which can include, a gamer device 106-A, anadministrator device 106-B, and/or a supervisor device 106-C. The userdevices 106 allow a user, including a gamer, a parent, and/or aneducator, including a teacher and/or an administrator, to access theevaluation and rectification system 100. This access can be in the formof the gamer receiving missions from the evaluation and rectificationsystem 100, the gamer providing information to the evaluation andrectification system 100, the gamer providing answers to the evaluationand rectification system 100, the gamer receiving an evaluation and/orindicator of progress within a mission and/or level of mastery of thesubject matter of the mission, an administrator receiving informationindicative of the functioning of the evaluation and rectification system100, the administrator providing updates and/or maintenance to theevaluation and rectification system 100, a supervisor such as, forexample, a parent, a teacher, and/or a counselor receiving informationfrom the evaluation and rectification system 100 indicative of gameractions within the evaluation and rectification system 100 and/or theevaluation of gamer actions within the evaluation and rectificationsystem 100. The details and function of the user devices 106 will bediscussed at greater length in reference to FIG. 1A below.

The evaluation and optimization system 100 can include one or severaldata aggregators 108. The data aggregators 108 can include anyelectronic information source, and can specifically, be a source ofinformation relating to the gamer. In some embodiments, the dataaggregators 108 can be a source of education related information, ofhealth related information, of demographic information, and/or ofpersonal information. The data aggregators 108 can be, for example, asocial network 108-A, a learning management system (LMS) 108-B, andeducation institution 108-C such as, for example, a school that thegamer is currently attending, will be attending, and/or has attended, anonline profile 108-D such as, for example, a gaming profile, a mediaconsumption profile, or any other profile of the gamer's habits,preferences, friends, or behavior, a source of medical records 108-Eincluding, for example, information relating to any gamer disabilityincluding a learning disability and/or any gamer mental health issue,and/or public records 108-F including, for example, information relatingto where the gamer lives. In some embodiments, for example, one orseveral of the data aggregators 108 can be an active part of theevaluation and rectification system 100 in that one or several of thedata aggregators can receive all or portions of the learning DNA fromthe evaluation and rectification system 100, as well as provideinformation relating to the gamer to the evaluation and rectificationsystem 100. In some embodiments, for example, one or several of the dataaggregators 108 can be a passive part of the evaluation andrectification system 100 in that the one or several of the dataaggregators do not receive all or portions of the learning DNA from theevaluation and rectification system 100. In some embodiments, a dataaggregator 108 is an active part of the evaluation and rectificationsystem 100 when the data aggregator receives information relating to thegamer from the evaluation and rectification system 100, and the dataaggregator 108 is a passive part of the evaluation and rectificationsystem 100 when the data aggregator 108 does not receive informationrelating to the gamer from the evaluation and rectification system 100.

The evaluation and rectification system 100 can include a network 110.The network 110 allows communication between the components of theevaluation and rectification system 100. The network 110 can be, forexample, a local area network (LAN), a wide area network (WAN), a wirednetwork, wireless network, a telephone network such as, for example, acellphone network, the Internet, the World Wide Web, or any otherdesired network. In some embodiments, the network 110 can use anydesired communication and/or network protocols.

With reference now to FIG. 1A, a block diagram of one embodiment of auser device 106 is shown. As discussed above, the user device 106 can beconfigured to provide and/or receive information to other components ofthe evaluation and rectification system 100. The user device can accessthe evaluation and rectification system 100 through any desired means ortechnology, including, for example, a webpage such as, for example, asocial network service page, or a web portal. As depicted in FIG. 1A,the user device 106 can include a network interface 120. The networkinterface 120 allows the user device 106 to access the other componentsof the evaluation and rectification system 100, and specifically allowsthe user device 106 to access the network 110 of the evaluation andrectification system 100. The network interface can include featuresconfigured to send and receive information, including, for example, anantenna, a modem, a transmitter, receiver, or any other feature that cansend and receive information. The network interface 120 can communicatevia telephone, cable, fiber-optic, or any other wired communicationnetwork. In some embodiments, the network interface 120 can communicatevia cellular networks, WLAN networks, or any other wireless network.

The user device 106 can include, for example, a mission engine 122. Themission engine 122 can receive mission data from the mission database104-B of the evaluation and rectification system 100, and can providethe mission to the gamer. In some embodiments, for example, the missionengine 122 can include, a video player, an audio player, and/or anyother software used to provide the mission to the gamer.

The user device 106 can include a learning DNA engine 124. The learningDNA engine 124 can receive user inputs including information forinclusion in the learning DNA database 104-A, and can specificallyreceive gamer inputs. The learning DNA engine 124 can evaluate the userdevice 106 for information, including gamer information for inclusion inthe learning DNA database 104-A. this evaluation can includeidentification of the user's online activities and retrieval ofinformation associated with these online activities. In someembodiments, for example, the learning DNA engine 124 can evaluate theuser device 106 for information, including gamer information identifyingdata aggregators 108 possessing information relating to the gamer, andcan be further configured to provide any collected information eitherfrom the user device 106 or from the user, such as the gamer, to thenetwork interface 124 providing to the other components of theevaluation and rectification system 100.

The user device 106 can include an evaluation engine 126. The evaluationengine 126 can receive user and/or gamer inputs provided as part of themission, and determine the correctness and/or incorrectness of thoseinputs. In some embodiments, for example, the evaluation engine 126 canreceive answer data to questions asked as part of the mission. Thisanswer data can then be used by the evaluation engine 126 to correctanswers provided by the gamer in response to mission questions, and toprovide the gamer with an evaluation of the mission outcome. In someembodiments, for example, the evaluation engine 126 can be configured toprovide information relating to the evaluation of the mission outcome tothe network interface 120, which provides the information relating tothe evaluation of the mission outcome to the other components of theevaluation and rectification system 100, and specifically to thelearning DNA database 104-A.

The user device 106 can include a user interface 202 that communicatesinformation to, and receives inputs from a user. The user interface 128can include a screen, a speaker, a monitor, a keyboard, a microphone, amouse, a touchpad, a keypad, or any other feature or features that canreceive inputs from a user and provide information to a user.

The user device 106 can include an update engine 130. The update enginecan be used, for example, by an administrator to update a portion of theevaluation and rectification system 100, and specifically to providemaintenance to the evaluation and rectification system 100 and/or toupdate all or portions of the missions database 104-B including, forexample, the updating of one or several of the missions.

With reference now to FIG. 2, a flowchart illustrating one embodiment ofa process 200 for generating learning DNA is shown. The process beginsat block 202 wherein a gamer account is generated. The gamer account caninclude identification information to allow the gamer to login to theevaluation and rectification system 100. Information relating to thegamer account can be stored in the learning DNA database 104-A.

After the gamer account is generated, the process 200 proceeds to block204 wherein gamer information is requested. In some embodiments, forexample, the request for gamer information can include, for example,prompting the gamer to answer questions relating to, for example, thegamer's name, age, grade level, past, current, and/or future classes,past and/or current grades, preferred learning style, or any otherdesired information relating to the gamer. In some embodiments, forexample, the gamer can enter the gamer information via the learning DNAengine 124. In some embodiments, for example, the learning DNA enginecan provide the gamer information to the network interface 120, whichnetwork interface 120 can communicate the gamer information to the othercomponents of the evaluation and rectification system 100 via thenetwork 110.

After the gamer information is requested, the process 200 proceeds toblock 206 wherein the learning DNA is created. In some embodiments, forexample, the learning DNA can be created from the gamer informationreceived from the user device 106. Specifically, in some embodiments,the learning DNA can be created by normalizing and organizing the gamerinformation. The learning DNA can be created by the processor 102

After the learning DNA is created, the process 200 proceeds to block 208wherein existing sources of gamer information are identified. In someembodiments, for example, existing sources of gamer information can beidentified by prompting the gamer to identify existing sources of gamerinformation. In some embodiments, for example, existing sources of gamerinformation can be identified by the learning DNA engine 124 searchingthe user device 106 for information, including gamer information forinclusion in the learning DNA database 104-A. In some embodiments, forexample, the learning DNA engine 124 can evaluate the user device 106for information, including gamer information identifying dataaggregators 108. In some embodiments, for example, the learning DNAengine can provide the existing sources of gamer information to thenetwork interface 120, which can then provide the information to theother components of evaluation and rectification system 100 via thenetwork 110. In some embodiments, for example, this information can bestored in the learning DNA database 104-A.

After the existing sources of gamer information are identified, theprocess 200 proceeds to block 210 wherein the gamer information iscollected from the existing sources of gamer information. In someembodiments, for example, these existing sources of gamer informationcan include, for example, the data aggregators 108. In some embodiments,the evaluation and rectification system 100 can be linked with the oneor several data aggregators 108 and/or can be integrated into one orseveral of the data aggregators 108. In such an embodiment, for example,a secure link and/or securable link between the data aggregators 108 ofthe other components of the evaluation and rectification system 100 canbe established. In some embodiments, for example, the secure link can beestablished using known secure communication protocols so as to allowthe verification of the source of any information request and the sourceof any information provided.

In some embodiments, for example, the processor 102 can, afterestablishing a secure connection with one or several of the dataaggregators 108, request information relating to the gamer from the oneor several data aggregators 108. In some embodiments, for example, thisrequest can include identification information for the gamer to allowthe data aggregator 108 to identify the subject to the query and anindicator of the type of information being requested.

After gamer information has been collected from existing sources suchas, for example, the data aggregators 108, the process 200 proceeds toblock 212 wherein the learning DNA is updated. In some embodiments, forexample, the learning DNA can be updated with gamer informationcollected from the existing sources. In some embodiments, the gamerinformation can be formatted and normalized so as to allow itsincorporation into the learning DNA. In some embodiments, for example,the gamer information collected from the existing sources can beorganized in formatted by the processor 102, and can be stored in thelearning DNA database 104-A.

After the learning DNA has been updated, the process 200 proceeds toblock 214 wherein mission information is received. In some embodiments,for example, mission information can include information relating to amission outcome and/or to a requested or completed mission. In someembodiments, for example, this mission information can identify thesubject of the mission, which subject of the mission can comprise aplurality of topics, the topic of the subject of the mission, whichtopic can comprise a plurality of subtopics, the subtopic of the topicof the mission, or any desired description of the information containedin the mission. In some embodiments, the subtopic of the topic of themission can be further divided and/or subdivided as desired to provide adesired level of granularity of the content of a mission. In someembodiments, for example, the mission information can include anindicator as to whether the mission was completed. In some embodimentsin which the mission was completed, the mission information can includean indicator of the outcome of a mission, such as, for example, agamer's mission score, an indicator of the subject matter of correctanswers, an indicator of the subject matter of incorrect answers, or anindicator of subject matter that should be repeated.

After the mission information is received, the process 200 proceeds toblock 216 wherein the learning DNA is updated with the missioninformation. In some embodiments, for example, the mission informationcan be can be formatted and normalized so as to allow its incorporationinto the learning DNA. In some embodiments, for example, the missioninformation can be organized in formatted by the processor 102, and canbe stored in the learning DNA database 104-A.

With reference now to FIG. 3, a flowchart illustrating one embodiment ofa process 300 for retrieving gamer information is shown. In someembodiments, the process 300 can be performed in the place of block 208and/or block 210 of FIG. 2. The process 300 can be performed by theevaluation and rectification system 100 and/or by a component thereof.

The process 300 begins at block 302 wherein the user's activity profileis retrieved. In some embodiments, the user's activity profile canidentify user activities on the user device 106 including, for example,the gamer device 106-A and/or on a device other than the user device 106that is utilized by the user to access the Internet and/or websites. Insome embodiments, the user's activity profile can comprise the user'sbrowsing history and/or any other record of Internet usage and/orwebsites visited by the user. In some embodiments, this information canbe retrieved from a web cache of an Internet browser on the user device106 and/or on another device. In one embodiment, for example, in whichthis information is retrieved from the user device 106, the user'sactivity profile can be found within the network interface 120.

After the user's activity profile has been retrieved, the process 300proceeds to block 304 wherein potential data sources are identified. Insome embodiments, this identification can be performed by the processor102 of the evaluation and rectification system 100 and/or by a componentof the user device 106. In some embodiments, this identification caninclude searching the information from the web cache for an indicationof websites to which the gamer provided information and with which thegamer had frequent and/or regular contact. In some embodiments, forexample, this identification can further include identifying known datasources such as, for example, social media websites and/or webpages,educational websites and/or webpages, discussion forums, medical serviceprovider websites and/or webpages, and the like. In some embodiments,the identification of potential data sources 108 can include adding ofinformation relating to the potential data sources 108 to a database104. In some embodiments, this information can include an identificationof a potential data source 108, and in some embodiments can include anidentification of a communication pathway with the potential data source108. In some embodiments, the communication pathway can be thecommunication protocol, communication channel, communication process,and/or the like by which the evaluation and rectification system 100 canprovide information to, and receive information from the data source108. In some embodiments, the communication pathway can include one orseveral of encryption and/or identification protocols to allow for theverification of the identity of the evaluation and rectification system100 and to protect the transmission of information from the data source108.

After potential data sources 108 have been identified, the process 300proceeds to block 306 wherein a data source 108 is selected. In someembodiments, the data source 108 can be selected by the processor 102 ofthe evaluation and rectification system 102 and/or by a component of theuser device 106. In some embodiments, the data source 108 can beselected from the database containing the identification of potentialdata sources 108. In some embodiments, the data source 108 can beselected based on any desired factor including, for example, thelikelihood of the data source 108 containing desired gamer information,the ease with which the data source 108 can be accessed, reliability ofthe data source 108, the level of security of the data source 108,and/or the ordering of the data sources 108 within the database. In oneembodiment, for example, the selected data source 108 can be the firstdata source within the database.

After the data source 108 is selected, the process 300 proceeds to block308 wherein user information is requested from the data source 108. Insome embodiments, for example, the user information can be requestedfrom the data source 108 by the processor 102 and/or by anothercomponent of the evaluation and rectification system 100, and theinformation can be requested via the network 110. In some embodiments,user information can be requested from the data source 108 via thecommunication pathway.

After the user information has been requested, the process 300 proceedsto block 310 wherein the user information is received. In someembodiments, the user information can be received via the network 110and can be received by, for example, the processor 102. In someembodiments, after the user information has been received and/or hasbeen requested, a binary value can be added to the database of datasources, and can be associated with the relevant data source 108, whichvalue can indicate that user information has been requested and/or hasbeen received from the associated data source 108.

After the user information has been received, the process 300 proceedsto decision state 312 wherein it is determined if there is an additionaldata source 108 in the database of data sources from which userinformation has not been requested and/or has not been received. In someembodiments, this determination can include review of the database ofdata sources to determine if any of the data sources 108 containedwithin the database are not associated with the value indicative of therequest for and/or receipt of user information from a data source 108.If it is determined that there are no additional data sources 108, thenthe process 300 proceeds to block 314 and continues to block 212 of FIG.2. If it is determined that there are additional data sources 108, thenthe process 300 returns to block 306 and continues with process 300 asdiscussed above.

With reference now to FIG. 4, a flowchart illustrating one embodiment ofa process 400 for recommending a mission is provided. The process beginsat block 402 wherein the learning DNA is received. In some embodiments,for example, the learning DNA can be received from the learning DNAdatabase 104-A.

After the learning DNA is received, the process 400 proceeds to block404 wherein the subject matter is identified. In some embodiments, forexample, the subject matter defines a group of related information. Insome embodiments, for example, the subject matter can correspond to acourse of study such as, for example, United States history, Europeanhistory, physics, chemistry, biology, math, algebra, trigonometry,advanced algebra, calculus, or any other course of study.

In some embodiments, for example, the subject matter can be identifiedbased on information contained within the learning DNA. Thus, forexample, the learning DNA can include a prioritized list of subjectmatters. This listing generated based on a variety of factors including,for example, gamer input indicating a prioritization, current, past,and/or planned gamer courses, and/or current and/or past gamer grades.In some embodiments, for example, the subject matter can be identifiedbased on a gamer selection of the subject matter.

After the subject matter is identified, the process 400 proceeds toblock 406 wherein the subject matter topic is identified. In someembodiments, for example, the subject matter topic is a group of relatedinformation within the subject. In some embodiments, for example, thesubject matter topic can correspond to a topic within a course of studysuch as, for example, the Civil War, the 60's, the Cold War, or WorldWar II within United States history or differential calculus or integralcalculus within calculus.

In some embodiments, for example, the subject matter topic can beidentified based on information contained within the learning DNA. Thus,for example, the learning DNA can include a prioritized list of subjectmatter topics. This listing can be generated based on a variety offactors including, for example, gamer input indicating a prioritization,current, past, and/or planned gamer courses, and/or current and/or pastgamer grades. In some embodiments, for example, the subject matter topiccan be identified based on a gamer selection of the subject mattertopic.

After the subject matter topic is identified, the process 400 proceedsto block 408 wherein the learning style is identified. In someembodiments, for example, the learning style represents a format oflearning and/or teaching such as, for example, visual, aural, verbal,physical, logical, social, or solitary. In some embodiments, forexample, the learning style can be identified based on informationcontained within the learning DNA. Thus, for example, the learning DNAcan include information relating to the gamers preferred learning styleor the relative effectiveness of different learning styles for thegamer. In some embodiments, for example, the learning style can be basedon the gamer's preferred learning style and/or the learning style thatis most effective for the gamer. In some embodiments, the learning stylecan be identified based on a gamer input.

After the learning style has been identified, the process 400 proceedsto block 410 wherein the mission is identified. As discussed above, themissions can include activities configured to teach a gamer someinformation, to teach a gamer a skill, to ascertain a gamer's mastery ofsome information and/or skill, to determine the effectiveness of one orseveral learning styles, to introduce the gamer to a new learning style,and/or to increase the ability of the gamer to learn with the learningstyle. The mission can be identified, for example, based on the learningDNA, and specifically based on the identified subject matter, theidentified subject matter topic, and the identified learning style. Insome embodiments, the mission can be identified from one or severalmissions stored within the missions database 104-B, and in someembodiments, the mission can be identified from one or several missionsstored in other components of the evaluation and rectification system100 such as, for example, the LMS 108-B and/or the education institution108-C.

After the mission has been identified, the process proceeds to decisionstate 412 wherein it is determined if the gamer has completed themission. In some embodiments, for example, the evaluation andrectification system 100 can receive an indicator of a mission beencompleted. In some embodiments, for example, the indication can beprovided by the mission engine 122 to the evaluation and rectificationsystem 100. In some embodiments, for example, this indication can bestored as part of the learning DNA database 104-A.

If it is determined that the mission is complete, the process 400proceeds to block 414 wherein the mission results are received. In someembodiments, for example, the mission results can be received by theevaluation and rectification system 100 from the user device 106. Insome embodiments, the mission results can be received from the missionengine 122 and/or the evaluation engine 126 via the network interface120 of the user device 106.

After the mission results are received, the process 400 proceeds toblock 416 wherein the mission results are evaluated. In someembodiments, for example, the mission results can be evaluated by theevaluation engine 126 of the user device 106, and in some embodiments,the mission results can be evaluated by the processor 102 of theevaluation and rectification system 100. In some embodiments, forexample, the mission results can be evaluated by both the evaluationengine 126 of the user device 106 and the processor 102 of theevaluation and rectification system 100. The mission results can beevaluated to determine the correctness and/or incorrectness of the gamerprovided answers. In some embodiments, for example, the mission data canbe evaluated to determine aspects of the mission that the gamer hasmastered, aspects of the mission that the gamer should repeat, and/or ascore for the mission.

After the mission results have been evaluated, and with reference againto decision state 412 if it is determined that the mission is notcomplete, the process 400 proceeds to block 418 wherein the learning DNAis updated. In some embodiments, for example, the learning DNA can beupdated with the mission results, and/or with information indicatingthat the mission was not completed. The learning DNA can be updatedwithin the learning DNA database 104-A.

With reference now to FIG. 5, a flowchart depicting one embodiment of aprocess 500 for identifying mission subject matter is depicted. In someembodiments, the process 500 can be used upon the creation of a newgamer account, and/or in the event of the existence of a gamer accountlacking all and/or substantial portions of the learning DNA. The process500 begins in block 502 wherein the learning DNA is received. In someembodiments, for example, the learning DNA can be received from thelearning DNA database 104-A.

After the learning DNA has been received, the process proceeds to block504 wherein the gamer age and grade is identified. In some embodiments,for example, the gamer's age and grade can be identified by requestingand receiving information from the gamer. In some embodiments, forexample, the processor 102 can send a request to the learning DNA engine124 of the user device 106 for the gamer age and grade information. Thelearning DNA engine 124 can request gamer age and grade information fromthe gamer via the user interface 128. In such an embodiment, thereceived gamer age and grade information can be returned to theprocessor 102 via the network interface 120 of the user device 106. Insome embodiments, the gamer age and grade information can be stored inthe learning DNA database 104-A.

After the gamer age and grade has been identified, the process 500proceeds to block 506 wherein the subject matter is identified. In someembodiments, the subject matter can be identified the of the receipt ofa gamer input identifying the subject matter. In some embodiments, theidentification of the subject matter can include retrieving a databaseof subjects. In some embodiments, for example, the processor 102 cansend a request to the learning DNA engine 124 of the user device 106 forsubject matter information. In some embodiments, for example, thelearning DNA engine 124 can request subject matter information from thegamer via the user interface 128, and can return the received subjectmatter information to the processor 102 via the network interface 120 ofthe user device 106. In some embodiments, the gamer identified subjectmatter can be stored in the learning DNA database 104-A.

In some embodiments, the databases of subjects can include informationidentifying a plurality of subjects and/or information identifying aplurality of conditions indicating the applicability of the subject toone or several categories of gamers. In one embodiment, for example, theconditions indicating the applicability of the subject one or severalcategories of gamers can identify criteria, which criteria can becontained in the learning DNA, which indicate the applicability of thesubject to a gamer. These criteria can identify, for example, an age ofthe gamer, a grade level the gamer, completed missions of the gamer,and/or the like. In some embodiments, a subgroup of the plurality ofsubjects in the database can be identified according to one or severalof the criteria. In some embodiments, this subgroup of subjects can bethe subgroup of subjects identified is relevant to a gamer based onportions and/or aspects of the learning DNA. In some embodiments, forexample, this subgroup can be identified according to at least one ofthe age of the gamer, the grade level of the gamer, the gameridentification, and/or any other information contained within thelearning DNA.

In some embodiments, the subgroup of subjects can be provided to theuser via the user device 106, and specifically via the user interface128. In some embodiments, the providing of the subgroup of subjects canfurther include the providing of a prompt to the user to select and/oridentify one of the subgroup of subjects. In some embodiments, theprocess 500 can include receiving an input identifying one of thesubgroup of the plurality of subjects. In some embodiments, thisidentified one of the subgroup of the plurality of subjects can containone or several topics.

After the subject matter has been identified, the process 500 proceedsto block 508 wherein subject matter topics are identified. In someembodiments, for example, subject matter topics can be identified byquerying the missions database 104-B for the subject matter topicsincluded in the subject matter. In some embodiments, for example,identifying the subject matter topics can further comprise identifyinggamer prompts providing an indication of the subject matter topic.

After the subject matter topics have been identified, the process 500proceeds to block 510 wherein a prompt for topic identification isprovided. In some embodiments, for example, the prompt for topicidentification can be provided to the gamer via the learning DNA engine124 of the user device 106 and the user interface 128 of the user device106. In some embodiments, for example, the user device 106 can providethe gamer with an indicator of subject matter topics that can, forexample, be a name of the subject matter topic and/or a portion of thecontent of the subject matter topic. In some embodiments, for example,the indicator of the subject matter topic can be accompanied with thequestion as to whether the gamer desires a mission related to theindicated subject matter topic. In some embodiments, the providing of aprompt for topic identification can further include receiving a userinput identifying a selected topic and/or one of the plurality of topicsprovided to the user. In some embodiments, this input can be receivedvia the user interface 128 of the user device 106.

After the prompt for topic identification is provided, the process 500proceeds to decision state 512 wherein it is determined whether thetopic is identified. In some embodiments, the topic can be identified bya gamer response to the prompt for topic identification. If the gamerresponse indicates of the subject matter topic of the prompt is not thecorrect and/or the desired subject matter topic, then the subject mattertopic has not been identified, and the process 500 returns to block 508.

If the gamer response indicates that the subject matter topic of theprompt is the correct subject matter topic, then the subject mattertopic has been identified and the process 500 proceeds to block 514wherein a prompt is provided for subtopic identification. In someembodiments, for example providing a prompt for subtopic identificationcan include identifying the subtopic. In some embodiments, for example,subtopic can be identified by querying the missions database 104-B forthe subtopics included in the subject matter topic of the subjectmatter. In some embodiments, for example, identifying the subtopic canfurther include identifying gamer prompts providing an indication of thesubject matter topic.

In some embodiments, for example, providing the prompt for subtopicidentification can include providing a prompt to the gamer via thelearning DNA engine 124 of the user device 106 and the user interface128 of the user device 106. In some embodiments, for example, the userdevice 106 can provide the gamer with an indicator of the subtopic thatcan, for example, be a name of the subtopic and/or a portion of thecontent of the subtopic. In some embodiments, for example, the indicatorof the subtopic can be accompanied with the question as to whether thegamer desires a mission related to the indicated subtopic.

After the prompt for subtopic identification is provided, the process400 proceeds to decision state 516 wherein it is determined whether thesubtopic is identified. In some embodiments, the subtopic can beidentified by a gamer response to the prompt for subtopicidentification. If the gamer response indicates that the subtopic of theprompt is not the correct and/or desired subtopic, then the subtopic hasnot been identified, and the process 500 returns to block 514.

If the gamer response indicates that the subtopic of the prompt is thecorrect subtopic, then the subtopic has been identified in the process500 proceeds to decision state 518 wherein it is determined if there areadditional subtopics. In some embodiments, for example, determiningwhether there are additional subtopics can include querying the missionsdatabase 104-B for information indicating whether the subtopics aredivided into further subtopics. If the subtopics are divided intofurther subtopics, then the process 500 returns to block 514.

If the subtopics are not divided into further subtopics, then theprocess 500 proceeds to block 520 wherein an evaluation test isgenerated. In some embodiments, for example, the evaluation test cancomprise a plurality of questions relating to the information of theidentified subtopic. In some embodiments, for example, the plurality ofquestions of the evaluation test can broadly encompass all or a portionof the information contained in the identified subtopic. In someembodiments, for example, the plurality of questions can be unrelatedexcept that they all pertain to information within the subtopic, and insome embodiments, the plurality of questions and/or some of theplurality of questions can be related in that an incorrect answer canlead to a plurality of questions configured to identify the reason whythey gamer provided an incorrect answer to the initial question.

After the evaluation test has been generated, the process 500 proceedsto block 522 wherein the test results are evaluated. In someembodiments, for example, the test results can be evaluated by theevaluation engine 126 of the user device, and in some embodiments, forexample, the test results can be evaluated by the processor 102 of theevaluation and rectification system 100. In some embodiments, forexample, the evaluation of the test results can provide an indication ofthe portions of the information of the subject matter that the gamer hasmastered and/or has not mastered.

After the test results of been evaluated, the process 500 proceeds toblock 524 wherein the learning DNA is updated. In some embodiments, forexample, the learning DNA can be updated with the results of theevaluation of the test results. In some embodiments, for example, thelearning DNA can be updated in the learning DNA database 104-A. afterthe learning DNA has been updated, the process 500 proceeds to block 526and proceeds to block 502 of FIG. 5.

With reference now to FIG. 6, a flowchart illustrating one embodiment ofa process 600 for identifying information desired for making a missionrecommendation is shown. In some embodiments, the process 600 can beused to identify information used by the evaluation and rectificationsystem 100 in recommending a mission and in identifying if any of thisidentified information is absent and/or missing from the learning DNA.The process 600 can be performed in the place of block 504 of FIG. 5. Insome embodiments, the process 600 can be performed by the evaluation andrectification system 100 and/or by a component thereof.

The process 600 begins in block 602 wherein information for missionrecommendation is identified. In some embodiments, this information caninclude an identification of the types and/or categories of informationused in making a mission recommendation. In some embodiments, the typesand/or categories of information used in making a mission recommendationcan match and/or correspond to the types of information stored and/orcaptured in learning DNA, and can, in some embodiments, be coterminouswith the types of information stored and/or captured in the learningDNA.

In some embodiments, some of the types and/or categories of informationused in making a mission recommendation can be more or less usefuland/or important in making the mission recommendation. Similarly, someof the types of information stored and/or captured in the learning DNAcan be more or less useful in making a mission recommendation. In someembodiments, the identification of information for missionrecommendation can include identifying the relative importance of thetypes and/or categories of information used in making omissionrecommendation.

In some embodiments, this information can be retrieved from the learningDNA database 104-A and/or one of the other databases 104. In someembodiments, the identification of information permission recommendationcan be performed by the processor 102.

After information for mission recommendation has been identified, theprocess 600 proceeds block 604 wherein the information contained withinthe learning DNA is identified. In some embodiments, for example, thiscan include identifying the actual information contained within thelearning DNA. In some embodiments, this information can be retrievedfrom the learning DNA database 104-A. For further distinction betweenthe information identified in block 602 and the information identifiedin block 604 of FIG. 6, the information identified in block 602 of FIG.6 is the identification of the type of information used and/or useful inmaking a mission recommendation, whereas the information identified inblock 604 of FIG. 6 is the actual information contained within thelearning DNA of a gamer.

After the learning DNA information has been identified, the process 600proceeds to block 606 wherein the information for mission recommendationis compared with the learning DNA information. In some embodiments, thiscomparison can identify portions of information used and/or useful inmaking mission recommendation that is/are not contained in and/or areinadequately contained in the learning DNA. In some embodiments, a firstindicator can be added to the types and/or categories of informationused in making a mission recommendation that are missing or absent from,and/or are inadequately present in the learning DNA, and in someembodiments, a second indicator can be added to the types and/orcategories of information used in making mission recommendation that arefound and/or are adequately found in the learning DNA. In someembodiments, the first and second indicators can be Boolean indicators,the second indicator corresponding to a “true” condition, and the firstindicator corresponding to a “false” condition. In some embodiments,these indicators can be stored within one of the databases 104including, for example, the learning DNA database 104-A and/or themissions database 104-B.

After information for mission recommendation is compared with thelearning DNA information, the process 600 proceeds to decision state 608wherein it is determined if any information is missing. In someembodiments, this can include retrieving indicators stored within one ofthe databases 104, and determining which of the types and/or categoriesof information used and/or useful in mission recommendation areassociated with the first indicator, which first indicator indicatesthat the corresponding information is missing from and/or isinadequately present in the learning DNA. If it is determined that noneof the information used and/or useful in making a mission determinationis missing from the learning DNA, then the process 600 proceeds to block610 and continues with block 404 of FIG. 4.

If it is determined that at least one of the types and/or categories ofinformation used and/or useful in making a mission determination ismissing from and/or is inadequately present in the learning DNA, thenthe process 600 proceeds to decision state 612 wherein it is determinedif the missing information can be received from the gamer, such as, forexample, received in response to a request for information. In someembodiments, for example, the missing information can be informationthat the gamer can know and can reliably provide. In some embodiments,this information can include, for example, the gamer's age, the gamer'saddress, the gamer's grade level, and/or the like. If it is determinedthat the missing information cannot be received via request, then theprocess 600 proceeds to block 614 and continues with block 506 of FIG.5.

If it is determined that the missing information can be received fromthe gamer in response to a request for more information, then theprocess 600 proceeds to block 616 wherein the missing information isrequested. In some embodiments, this request can comprise anidentification of the missing information and a prompt to the gamer toprovide the missing information. In some embodiments, this request canbe performed by the evaluation and rectification system 100, andspecifically by the user interface 128 of the user device 106.

After the missing information has been requested, the process 600proceeds to block 618 wherein the requested information is received. Insome embodiments, this information can be received via a component ofthe evaluation and rectification system 100 such as, for example, theuser interface 128 of the user device 106. After the requestedinformation has been received, the process 600 returns to decision state608 and continues as outlined above.

With reference now to FIG. 7, flowchart illustrating one embodiment of aprocess 700 for generating an evaluation is shown. The process 700 canbe performed in the place of block 520 of FIG. 5. In some embodiments,the process 700 can be performed by the evaluation and rectificationsystem 100 and/or by a component thereof.

The process 700 begins at block 702 wherein a subtopic identification isreceived. In some embodiments, the subtopic can comprise a group ofmaterial, a plurality of which subtopics can form a topic. In someembodiments, the identification of the subtopic can be performed in 514of FIG. 5. After the subtopic identification has been received, theprocess 700 proceeds to block 704 wherein questions associated with thesubtopic are received. In some embodiments, these questions can bereceived from a component of the evaluation and rectification system 100including, for example, one of the databases 104, one of the userdevices 106, and/or one of the data sources 108.

After the questions have been received, the process 700 proceeds toblock 706 wherein information categories are identified within theidentified subtopic. In some embodiments, these information categoriescan correspond to the content of the one or several missions associatedwith the subtopic. In some embodiments, these information categories canbe stored within one of the databases 104 such as, for example, themissions database 104-B.

After the information categories have been identified, the process 700proceeds to block 708 wherein questions corresponding to the informationcategories are selected. In some embodiments, for example, one orseveral of the received questions can correspond to one or several ofthe information categories. In some embodiments, however, fewer than allof the received questions can be used in the creation of an evaluation,and thus, some subset of the received questions can be selected. In someembodiments, this subset can be selected based on the details of, forexample, the gamer's learning DNA. In some embodiments, this subset canbe identified by the application of a first indicator to selectedquestions and the second indicator to questions that are not selected.In some embodiments, these indicators can be stored in one of thedatabases 104 such as, for example, the missions database 104-B.

After the questions have been selected, the process 700 proceeds todecision state 710 wherein it is determined if the identifiedinformation categories are adequately covered by the selected questions.In some embodiments, for example, this can include determining whetherone or several questions has been selected for some or all of theidentified information categories. If it is determined that not all ofthe information categories are covered and/or are not adequatelycovered, then the process 700 returns to block 706.

If it is determined that all the information categories are coveredand/or are adequately covered, then the process 700 proceeds to block712 wherein the questions are compiled. In some embodiments, this caninclude, determining which of the received questions have been selected,and grouping the selected questions together into a single database. Insome embodiments, this compilation can include the retrieval ofindicators stored within one of the databases 104, and an identificationof questions associated with the first indicator.

After the questions of been compiled, the process 700 proceeds to block714 wherein the questions are provided to the gamer. In someembodiments, for example, this can include providing the compiledquestions to the gamer via the user device 106, and specifically via theuser interface 128 of the user device 106. After the questions have beenprovided to the user, the process 700 proceeds to block 716 andcontinues with block 522 of FIG. 5.

With reference now to FIG. 8, a flowchart illustrating one embodiment ofa process 800 for identifying a learning style is depicted. The process800 begins in block 802 where the learning DNA is received. In someembodiments, for example, the learning DNA can be received from theearning DNA database 104-A.

After the learning DNA has been received, the process 800 proceeds toblock 804 wherein a prompt is provided for learning style information.In some embodiments, for example, the prompt for learning styleinformation can be provided to the gamer via the learning DNA engine 124of the user device 106 and/or the user interface 128 of the user device106. In some embodiments, for example, the user device 106 can providethe gamer with an indicator of learning styles that can be, for example,a name of the learning style and/or an example of the learning style. Insome embodiments, for example, the indicator of the learning style canbe accompanied with the question as to whether the indicated learningstyle is the desired and/or preferred learning style.

After the prompt is provided for learning style information, the process800 proceeds to block 806 wherein gamer input is received. In someembodiments, for example, the gamer input can comprise an indicator ofthe desired and/or preferred learning style. In some embodiments, forexample, the gamer input can be received via the user interface 128 ofthe user device 106.

After the gamer input is received, the process 800 proceeds to block 808wherein the learning DNA is updated with the gamer input. In someembodiments, for example, the user interface 128 can provide the gamerinput to the network interface 120 which can provide the gamer input tothe evaluation and rectification system 100, and specifically to theprocessor 102 of the evaluation and rectification system 100. In someembodiments, for example, this gamer input can be incorporated into thelearning DNA and the learning DNA database 104-A can be updated.

After the learning DNA has been updated with the gamer input, theprocess 800 proceeds to block 810 wherein the learning DNA is evaluatedfor learning style information. In some embodiments, the learning DNAcan include an indicator of the preferred and/or relatively moreeffective learning style. In some embodiments, this indicator can bestored in the learning DNA in the learning DNA database 104-A. In someembodiments, for example, the evaluation of the learning DNA forlearning style information can include retrieving the learning DNA fromthe learning DNA database 104-A and retrieving the indicator of thepreferred and/or relatively more effective learning style from thelearning DNA by, for example, the processor 102.

After the learning DNA has been evaluated for learning styleinformation, the process 800 proceeds to block 812 wherein the learningstyle information is compared to any received mission results. In someembodiments, the mission results can include the effectiveness of alearning style in leading to the gamer's mastery of the informationassociated with the mission. In some embodiments, for example, the gamercan be given a mission for the purpose of ascertaining the effectivenessof a learning style. In such an embodiment, a non-preferred learningstyle may be incorporated into the mission, and the relativeeffectiveness of the non-preferred learning style can be ascertained bycomparing the evaluation the mission results to the evaluation ofmission results for missions incorporating the preferred learning style.

After the learning style information is compared to mission results, theprocess 800 proceeds to decision state 814 wherein it is determined ifthe gamer preferred learning style or the non-preferred learning styleassociated with the gamer completed mission is more effective. If it isdetermined that the learning style associated with the gamer completedmission is more effective than they gamer preferred learning style, thenthe process 800 can proceed to block 816 wherein the learning DNA can beupdated to indicate the more effective learning style. In someembodiments, for example, the learning DNA can be updated in thelearning DNA database 104-A.

After the learning DNA has been updated, or if it is determined atdecision state 814 that the gamer preferred learning style is moreeffective than the learning style associated with the gamer completedmission, then the process 800 proceeds to decision state 818 wherein itis determined if additional learning style analysis will be performed.In some embodiments, for example, additional learning style analysis canbe performed to evaluate the effectiveness of further learning styles.If it is determined that additional analysis will not be performed, thenthe process in terminate.

If it is determined that additional analysis will be performed, theprocess 800 proceeds to block 820 wherein an additional learning styleevaluation mission is requested. In some embodiments, the learning styleevaluation mission can be configured to allow the evaluation of theeffectiveness of a previously non-evaluated learning style and/or toallow the further collection of data relating to a previously evaluatedlearning style. After the additional learning style evaluation isrequested, the process 800 proceeds to block 822 and proceeds to block410 of FIG. 4.

With reference now to FIG. 9, an exemplary environment with whichembodiments may be implemented is shown with a computer system 900 thatcan be used by a user 904 as all or a component of the evaluation andrectification system 100. The computer system 900 can include a computer902, keyboard 922, a network router 912, a printer 908, and a monitor906. The monitor 906, processor 902 and keyboard 922 are part of acomputer system 926, which can be a laptop computer, desktop computer,handheld computer, mainframe computer, etc. The monitor 906 can be aCRT, flat screen, etc.

A user 904 can input commands into the computer 902 using various inputdevices, such as a mouse, keyboard 922, track ball, touch screen, etc.If the computer system 900 comprises a mainframe, a designer 904 canaccess the computer 902 using, for example, a terminal or terminalinterface. Additionally, the computer system 926 may be connected to aprinter 908 and a server 910 using a network router 912, which mayconnect to the Internet 918 or a WAN.

The server 910 may, for example, be used to store additional softwareprograms and data. In one embodiment, software implementing the systemsand methods described herein can be stored on a storage medium in theserver 910. Thus, the software can be run from the storage medium in theserver 910. In another embodiment, software implementing the systems andmethods described herein can be stored on a storage medium in thecomputer 902. Thus, the software can be run from the storage medium inthe computer system 926. Therefore, in this embodiment, the software canbe used whether or not computer 902 is connected to network router 912.Printer 908 may be connected directly to computer 902, in which case,the computer system 926 can print whether or not it is connected tonetwork router 912.

With reference to FIG. 10, an embodiment of a special-purpose computersystem 1004 is shown. The above methods may be implemented bycomputer-program products that direct a computer system to perform theactions of the above-described methods and components. Each suchcomputer-program product may comprise sets of instructions (codes)embodied on a computer-readable medium that directs the processor of acomputer system to perform corresponding actions. The instructions maybe configured to run in sequential order, or in parallel (such as underdifferent processing threads), or in a combination thereof. Afterloading the computer-program products on a general purpose computersystem 926, it is transformed into the special-purpose computer system1004.

Special-purpose computer system 1004 comprises a computer 902, a monitor906 coupled to computer 902, one or more additional user output devices1030 (optional) coupled to computer 902, one or more user input devices1040 (e.g., keyboard, mouse, track ball, touch screen) coupled tocomputer 902, an optional communications interface 1050 coupled tocomputer 902, a computer-program product 1005 stored in a tangiblecomputer-readable memory in computer 902. Computer-program product 1005directs system 1004 to perform the above-described methods. Computer 902may include one or more processors 1060 that communicate with a numberof peripheral devices via a bus subsystem 1090. These peripheral devicesmay include user output device(s) 1030, user input device(s) 1040,communications interface 1050, and a storage subsystem, such as randomaccess memory (RAM) 1070 and non-volatile storage drive 1080 (e.g., diskdrive, optical drive, solid state drive), which are forms of tangiblecomputer-readable memory.

Computer-program product 1005 may be stored in non-volatile storagedrive 1080 or another computer-readable medium accessible to computer902 and loaded into memory 1070. Each processor 1060 may comprise amicroprocessor, such as a microprocessor from Intel® or Advanced MicroDevices, Inc.®, or the like. To support computer-program product 1005,the computer 902 runs an operating system that handles thecommunications of product 1005 with the above-noted components, as wellas the communications between the above-noted components in support ofthe computer-program product 1005. Exemplary operating systems includeWindows® or the like from Microsoft® Corporation, Solaris® from Oracle®,LINUX, UNIX, and the like.

User input devices 1040 include all possible types of devices andmechanisms to input information to computer system 902. These mayinclude a keyboard, a keypad, a mouse, a scanner, a digital drawing pad,a touch screen incorporated into the display, audio input devices suchas voice recognition systems, microphones, and other types of inputdevices. In various embodiments, user input devices 1040 are typicallyembodied as a computer mouse, a trackball, a track pad, a joystick,wireless remote, a drawing tablet, a voice command system. User inputdevices 1040 typically allow a user to select objects, icons, text andthe like that appear on the monitor 906 via a command such as a click ofa button or the like. User output devices 1030 include all possibletypes of devices and mechanisms to output information from computer 902.These may include a display (e.g., monitor 906), printers, non-visualdisplays such as audio output devices, etc.

Communications interface 1050 provides an interface to othercommunication networks 1095 and devices and may serve as an interface toreceive data from and transmit data to other systems, WANs and/or theInternet 918. Embodiments of communications interface 1050 typicallyinclude an Ethernet card, a modem (telephone, satellite, cable, ISDN), a(asynchronous) digital subscriber line (DSL) unit, a FireWire®interface, a USB® interface, a wireless network adapter, and the like.For example, communications interface 1050 may be coupled to a computernetwork, to a FireWire® bus, or the like. In other embodiments,communications interface 1050 may be physically integrated on themotherboard of computer 902, and/or may be a software program, or thelike.

RAM 1070 and non-volatile storage drive 1080 are examples of tangiblecomputer-readable media configured to store data such ascomputer-program product embodiments of the present invention, includingexecutable computer code, human-readable code, or the like. Other typesof tangible computer-readable media include floppy disks, removable harddisks, optical storage media such as CD-ROMs, DVDs, bar codes,semiconductor memories such as flash memories, read-only-memories(ROMs), battery-backed volatile memories, networked storage devices, andthe like. RAM 1070 and non-volatile storage drive 1080 may be configuredto store the basic programming and data constructs that provide thefunctionality of various embodiments of the present invention, asdescribed above.

Software instruction sets that provide the functionality of the presentinvention may be stored in RAM 1070 and non-volatile storage drive 1080.These instruction sets or code may be executed by the processor(s) 1060.RAM 1070 and non-volatile storage drive 1080 may also provide arepository to store data and data structures used in accordance with thepresent invention. RAM 1070 and non-volatile storage drive 1080 mayinclude a number of memories including a main random access memory (RAM)to store of instructions and data during program execution and aread-only memory (ROM) in which fixed instructions are stored. RAM 1070and non-volatile storage drive 1080 may include a file storage subsystemproviding persistent (non-volatile) storage of program and/or datafiles. RAM 1070 and non-volatile storage drive 1080 may also includeremovable storage systems, such as removable flash memory.

Bus subsystem 1090 provides a mechanism to allow the various componentsand subsystems of computer 902 communicate with each other as intended.Although bus subsystem 1090 is shown schematically as a single bus,alternative embodiments of the bus subsystem may utilize multiple bussesor communication paths within the computer 902.

A number of variations and modifications of the disclosed embodimentscan also be used. Specific details are given in the above description toprovide a thorough understanding of the embodiments. However, it isunderstood that the embodiments may be practiced without these specificdetails. For example, well-known circuits, processes, algorithms,structures, and techniques may be shown without unnecessary detail inorder to avoid obscuring the embodiments.

Implementation of the techniques, blocks, steps and means describedabove may be done in various ways. For example, these techniques,blocks, steps and means may be implemented in hardware, software, or acombination thereof. For a hardware implementation, the processing unitsmay be implemented within one or more application specific integratedcircuits (ASICs), digital signal processors (DSPs), digital signalprocessing devices (DSPDs), programmable logic devices (PLDs), fieldprogrammable gate arrays (FPGAs), processors, controllers,micro-controllers, microprocessors, other electronic units designed toperform the functions described above, and/or a combination thereof.

Also, it is noted that the embodiments may be described as a processwhich is depicted as a flowchart, a flow diagram, a swim diagram, a dataflow diagram, a structure diagram, or a block diagram. Although adepiction may describe the operations as a sequential process, many ofthe operations can be performed in parallel or concurrently. Inaddition, the order of the operations may be re-arranged. A process isterminated when its operations are completed, but could have additionalsteps not included in the figure. A process may correspond to a method,a function, a procedure, a subroutine, a subprogram, etc. When a processcorresponds to a function, its termination corresponds to a return ofthe function to the calling function or the main function.

Furthermore, embodiments may be implemented by hardware, software,scripting languages, firmware, middleware, microcode, hardwaredescription languages, and/or any combination thereof. When implementedin software, firmware, middleware, scripting language, and/or microcode,the program code or code segments to perform the necessary tasks may bestored in a machine readable medium such as a storage medium. A codesegment or machine-executable instruction may represent a procedure, afunction, a subprogram, a program, a routine, a subroutine, a module, asoftware package, a script, a class, or any combination of instructions,data structures, and/or program statements. A code segment may becoupled to another code segment or a hardware circuit by passing and/orreceiving information, data, arguments, parameters, and/or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, etc.

For a firmware and/or software implementation, the methodologies may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. Any machine-readable mediumtangibly embodying instructions may be used in implementing themethodologies described herein. For example, software codes may bestored in a memory. Memory may be implemented within the processor orexternal to the processor. As used herein the term “memory” refers toany type of long term, short term, volatile, nonvolatile, or otherstorage medium and is not to be limited to any particular type of memoryor number of memories, or type of media upon which memory is stored.

Moreover, as disclosed herein, the term “storage medium” may representone or more memories for storing data, including read only memory (ROM),random access memory (RAM), magnetic RAM, core memory, magnetic diskstorage mediums, optical storage mediums, flash memory devices and/orother machine readable mediums for storing information. The term“machine-readable medium” includes, but is not limited to portable orfixed storage devices, optical storage devices, and/or various otherstorage mediums capable of storing that contain or carry instruction(s)and/or data.

While the principles of the disclosure have been described above inconnection with specific apparatuses and methods, it is to be clearlyunderstood that this description is made only by way of example and notas limitation on the scope of the disclosure.

What is claimed is:
 1. A method of updating learning DNA, the methodcomprising: retrieving learning DNA from a learning DNA database,wherein the learning DNA comprises a gamer age, a gamer education level,gamer subjects, and the gamer's past mission results, wherein the gamersubjects include an identification of a group of subject matter that thegamer has mastered and an identification of a group of subject matterthat the gamer has partially mastered; identifying a subject matter fromthe learning DNA retrieved from the learning DNA database, wherein thesubject matter defines a group of related information; identifying asubject matter topic, wherein the subject matter topic comprises a groupof related information within the subject; retrieving a mission from amission database, wherein the mission comprises at least one learningactivity; determining if the mission is complete; and updating thelearning DNA in the learning DNA database, wherein updating the learningDNA comprises determining whether the mission was successfullycompleted, and wherein updating the learning DNA comprises outputting avalue indicating whether the mission was successfully completed to thelearning DNA database.
 2. The method of claim 1, wherein the group ofrelated information corresponds to a course of study.
 3. The method ofclaim 1, wherein the learning DNA comprises a prioritized list ofsubject matter, and wherein the identified subject matter is selectedbased on the prioritized list of subject matter.
 4. The method of claim1, wherein the subject matter topic is identified based on informationcontained in the learning DNA.
 5. The method of claim 4, wherein thelearning DNA comprises a prioritized list of subject matter topics, andwherein the identified subject matter topic is selected based on theprioritized list of subject matter topics.
 6. The method of claim 1,further comprising receiving the mission results, wherein the missionresults are received from a user device.
 7. A method of identifying alearning style, the method comprising: retrieving learning DNA from alearning DNA database, the learning DNA comprising a gamer age, a gamereducation level, gamer subjects, and the gamer's past mission results,wherein the gamer subjects include an identification of a group ofsubject matter that the gamer has mastered and an identification of agroup of subject matter that the gamer has partially mastered; receivingan input identifying a learning style; updating the learning DNA withthe identified learning style, wherein updating the learning DNAcomprises outputting an update to the learning DNA database; receivingat least one mission result for at least one completed mission, whereinthe mission comprises at least one learning activity, and wherein themission result indicates the effectiveness of a mission learning style;comparing the identified learning style and the mission results todetermine if the identified learning style corresponds to the missionlearning style; and updating the learning DNA if the identified learningstyle does not correspond to the mission learning style, whereinupdating the learning DNA comprises outputting an update to the learningDNA database.
 8. The method of claim 7, wherein the mission resultsindicate the effectiveness with which one or several learning stylesmaster the at least one activity of the mission.
 9. The method of claim7 further comprising determining to evaluate the effectiveness of asecond learning style compared to the identified learning style.
 10. Themethod of claim 9, further comprising selecting a mission to evaluatethe effectiveness of the second learning style compared to theidentified learning style.
 11. The method of claim 7, further comprisingselecting a mission having a subject matter corresponding to an aspectof the learning DNA.
 12. The method of claim 7, wherein receiving themission result comprises receiving a plurality of gamer responsescorresponding to questions contained in the mission.
 13. The method ofclaim 12, wherein receiving the mission result further comprises:identifying correctly answered questions, and identifying incorrectlyanswered questions.
 14. A system for identifying a learning style, thesystem comprising: memory storing a plurality of missions and configuredto store learning DNA in a learning DNA database; and a processorconfigured to: retrieve learning DNA from the learning DNA database, thelearning DNA comprising a gamer age, a gamer education level, gamersubjects, and the gamer's past mission results, wherein the gamersubjects include an identification of a group of subject matter that thegamer has mastered and an identification of a group of subject matterthat the gamer has partially mastered; receive an input identifying alearning style; update the learning DNA with the identified learningstyle, wherein updating the learning DNA comprises outputting an updateto the learning DNA database; receive at least one mission result for atleast one completed mission, wherein the mission comprises at least onelearning activity, and wherein the mission result indicates theeffectiveness of a mission learning style; compare the identifiedlearning style and the mission results to determine if the identifiedlearning style corresponds to the mission learning style; and update thelearning DNA if the identified learning style does not correspond to themission learning style, wherein updating the learning DNA comprisesoutputting an update to the learning DNA database.
 15. The system ofclaim 14, wherein the mission results indicate the effectiveness withwhich one or several learning styles master the at least one activity ofthe mission.
 16. The system of claim 14 wherein the processor is furtherconfigured to determine to evaluate the effectiveness of a secondlearning style compared to the identified learning style.
 17. The systemof claim 16, wherein the processor is further configured to select amission to evaluate the effectiveness of the second learning stylecompared to the identified learning style.
 18. The system of claim 14,wherein the processor is further configured to select a mission having asubject matter corresponding to an aspect of the learning DNA.
 19. Thesystem of claim 14, further comprising a user device connected to theprocessor via a network, wherein the user device is configured toreceive a gamer input indicating the identified learning style.